We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byLarissa Darsey
Modified over 2 years ago
# Name of the algorithm used to construct the model. Algorithm = DistanceToAverage Parameter = MaxDist 0.2 Species = lobo guara
# Name of the algorithm used to construct the model. Algorithm = DG_GARP_BS Parameter = CommissionSampleSize 10000 Parameter = CommissionThreshold 50 Parameter = ConvergenceLimit 0.01 Parameter = HardOmissionThreshold 100 Parameter = MaxGenerations 400 Parameter = MaxThreads 1 Parameter = ModelsUnderOmissionThreshold 20 Parameter = PopulationSize 50 Parameter = Resamples 2500 Parameter = TotalRuns 100 Parameter = TrainingProportion 0.5 Species = lobo guara
#Minimum distance Algorithm = MinimumDistance Parameter = MaxDist 0.1 Species = furcata boliviana
#Bioclimatic Envelop Algorithm = Bioclim Parameter = StandadDeviationCutoff 0.674 Species = furcata boliviana
#Bioclimatic Envelop using distance to average Algorithm = Bioclim Distance Parameter = StandadDeviationCutoff 0.674 Species = furcata boliviana
# Climate Space Model - Broken-Stick Algorithm = CSMBS Parameter = Randomisations 8 Parameter = RandomiserRepeats 50 Parameter = StandardDeviations 0.05 Parameter = MinComponents 2 Parameter = MaxAttempts 1 Species = furcata boliviana
# GARP: Genetic Algorithm for Rule Set Production Algorithm = GARP Parameter = MaxGenerations 100 Parameter = ConvergenceLimit 0.05 Parameter = Resamples 2500 Parameter = MutationRate 0.25 Parameter = CrossoverRate 0.25 Species = furcata boliviana
# GARP with Best Subsets Procedure Algorithm = GARP_BS Parameter = TrainingProportion 0.5 Parameter = TotalRuns 10 Parameter = HardOmissionThreshold 100 Parameter = ModelsUnderOmissionThreshold 20 Parameter = CommissionThreshold 50 Parameter = CommissionSampleSize 10000 Parameter = MaxThreads 5 Parameter = MaxGenerations 20 Parameter = ConvergenceLimit 0.05 Parameter = PopulationSize 50 Parameter = Resamples 2500 Parameter = MutationRate 0.25 Parameter = CrossoverRate 0.25 Species = furcata boliviana
# Distance to average Algorithm = DistanceToAverage Parameter = MaxDist 0.1 Species = furcata boliviana
A performance evaluation approach openModeller: A Framework for species distribution Modelling.
Museum and Institute of Zoology PAS Warsaw Magdalena Żytomska Berlin, 6th September 2007.
A new tool for fundamental niche modelling Renato De Giovanni Centro de Referência em Informação Ambiental, CrIA.
Niches, Interactions and Movements. Calculating a Species Distribution Range Jorge Soberon M. A. Townsend Peterson.
$100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300.
State-of-the art in Croatia. National policies Country context toward EU climate and energy golas through building renovation projects Heat energy.
Climate Change Projections: The case of the Volcano Rabbit Angélica Domínguez & Enrique Martínez Meyer.
Candidate KBA Identification: Modeling Techniques for Field Survey Prioritization Species Distribution Modeling: approximation of species ecological niche.
Example projects using metadata and thesauri: the Biodiversity World Project Richard White Cardiff University, UK
Bioclimatic Modelling BIOCLIM Arthur D. Chapman Kakadu National Park.
At Reading Frank Bisby, Alistair Culham, Paul Valdes, Neil Caithness, Tim Sutton, Peter Brewer At Cardiff Alec Gray, Andrew Jones, Nick Fiddian, Nick Pittas,
NR 422- Habitat Suitability Models Jim Graham Spring 2009.
At Reading Frank Bisby, Alistair Culham, Neil Caithness, Tim Sutton, Peter Brewer, Chris Yesson At Cardiff Alec Gray, Andrew Jones, Nick.
Applications of Genetic Algorithms TJHSST Computer Systems Lab By Mary Linnell.
Mapping distributions of marine organisms using environmental niche modelling - AquaMaps K. Kaschner, J. Ready, S. Kullander, R. Froese and many more….INCOFISH,
Computer Science Genetic Algorithms10/13/10 1 An Investigation of Niching and Species Formation in Genetic Function Optimization Kalyanmoy Deb David E.
Evolving RBF Networks via GP for Estimating Fitness Values using Surrogate Models Ahmed Kattan Edgar Galvan.
Staging of the Ecological Niche Modeling Mammal Prototype Project Deana Pennington University of New Mexico December 14, 2004.
Learning Behavior using Genetic Algorithms and Fuzzy Logic GROUP #8 Maryam Mustafa Sarah Karim
Bioinformatics GIS Applications Anatoly Petrov.
Topological Data Analysis MATH 800 Fall Topological Data Analysis (TDA) An ε-chain is a finite sequence of points x 1,..., x n such that |x i –
Content Based Image Clustering and Image Retrieval Using Multiple Instance Learning Using Multiple Instance Learning Xin Chen Advisor: Chengcui Zhang Department.
AquaMaps Predictive distribution maps for marine organisms K. Kaschner, J. S. Ready, E. Agbayani, J. Rius, K. Kesner-Reyes, P. D. Eastwood, A. B. South,
EFFECTS OF CHANGING CLIMATE ON THE DEMOGRAPHY OF THE KARNER BLUE BUTTERFLY: PROGRESS SUMMARY NPS Climate change response grant A joint collaboration between.
Genetic Algorithm What is a genetic algorithm? “Genetic Algorithms are defined as global optimization procedures that use an analogy of genetic evolution.
Ali Husseinzadeh Kashan Spring 2010
GARP Genetic Algorithm for Rule-set Production
Optimizing genetic algorithm strategies for evolving networks Matthew Berryman.
O(N 1.5 ) divide-and-conquer technique for Minimum Spanning Tree problem Step 1: Divide the graph into N sub-graph by clustering. Step 2: Solve each.
Intro to AI Genetic Algorithm Ruth Bergman Fall 2002.
Procedures for managing workflow components Workflow components: A workflow can usually be described using formal or informal flow diagramming techniques,
A Virtual Laboratory for Global Biodiversity Analysis.
Aim in building a phylogenetic tree is to use a knowledge of the characters of organisms to build a tree that reflects the relationships between them.
Ensemble Methods An ensemble method constructs a set of base classifiers from the training data Ensemble or Classifier Combination Predict class label.
Tree-Building. Methods in Tree Building Phylogenetic trees can be constructed by: clustering method optimality method.
Is it possible to move Earth? Describe some of the ways it could be done
Debrup Chakraborty Non Parametric Methods Pattern Recognition and Machine Learning.
Sea Surface Temperature Changes & Biogeographic Ranges of Commercial Marine Species Canadian Climate Change Impacts & Adaptation Program Project A515 &
The Use of Linkage Learning in Genetic Algorithms By David Newman.
Phylogenetic Trees - Parsimony Tutorial #13
Jens Zimmermann, MPI für Physik München, ACAT 2005 Zeuthen1 Backups Jens Zimmermann Max-Planck-Institut für Physik, München Forschungszentrum.
June 2012 Spatial Data Cleaning Species Occurrence Data Arthur D. Chapman.
Adaptive Cruise Control (ACC)
1 Bresenham’s Circle Algorithm Define:D(s i ) = distance of p 3 from circle D(t i ) = distance of p 2 from circle i.e.D(s i ) = (x i + 1) 2 + y i 2 – r.
EXERCISES for ALGORITHMS WRITING
Ensemble Based Systems in Decision Making Advisor: Hsin-His Chen Reporter: Chi-Hsin Yu Date: IEEE CIRCUITS AND SYSTEMS MAGAZINE 2006, Q3 Robi.
Execution Control with If/Else and Boolean Questions Part 1 Alice.
© 2017 SlidePlayer.com Inc. All rights reserved.